Silver Standard Masks for Data Augmentation Applied to Deep-Learning-Based Skull-Stripping

The bottleneck of convolutional neural networks (CNN) for medical imaging is the number of annotated data required for training. Manual segmentation is considered to be the "gold-standard". However, medical imaging datasets with expert manual segmentation are scarce as this step is time-consuming and expensive. We propose in this work the use of what we refer to as silver standard masks for data augmentation in deep-learning-based skull-stripping also known as brain extraction. We generated the silver standard masks using the consensus algorithm Simultaneous Truth and Performance Level Estimation (STAPLE). We evaluated CNN models generated by the silver and gold standard masks. Then, we validated the silver standard masks for CNNs training in one dataset, and showed its generalization to two other datasets. Our results indicated that models generated with silver standard masks are comparable to models generated with gold standard masks and have better generalizability. Moreover, our results also indicate that silver standard masks could be used to augment the input dataset at training stage, reducing the need for manual segmentation at this step

Iamxt: max-tree toolbox for image processing and analysis

The iamxt is an array-based max-tree toolbox implemented in Python using the NumPy library for array processing. It has state of the art methods for building and processing the max-tree, and a large set of visualization tools that allow to view the tree and the contents of its nodes. The array-based programming style and max-tree representation used in the toolbox make it simple to use. The intended audience of this toolbox includes mathematical morphology students and researchers that want to develop research in the field and image processing researchers that need a toolbox simple to use and easy to integrate in their applications68184CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP311228/2014-32013/23514-0; 2013/07559-

Open-source tool for Airway Segmentation in Computed Tomography using 2.5D Modified EfficientDet: Contribution to the ATM22 Challenge

Airway segmentation in computed tomography images can be used to analyze pulmonary diseases, however, manual segmentation is labor intensive and relies on expert knowledge. This manuscript details our contribution to MICCAI's 2022 Airway Tree Modelling challenge, a competition of fully automated methods for airway segmentation. We employed a previously developed deep learning architecture based on a modified EfficientDet (MEDSeg), training from scratch for binary airway segmentation using the provided annotations. Our method achieved 90.72 Dice in internal validation, 95.52 Dice on external validation, and 93.49 Dice in the final test phase, while not being specifically designed or tuned for airway segmentation. Open source code and a pip package for predictions with our model and trained weights are in https://github.com/MICLab-Unicamp/medseg.Comment: Open source code, graphical user interface, and a pip package for predictions with our model and trained weights are in https://github.com/MICLab-Unicamp/medse

Understanding the conformational behaviour of Ac-Ala-NHMe in different media. A joint NMR and DFT study.

The authors thank EaStCHEM, CNPq and FAPESP for the studentship (to R.A.C. #2011/01170-1, FAPESP), as is CNPq for the fellowship (R.R.).The conformational behaviour of Ac-Ala-NHMe was studied for the compound in the gas-phase and in solution by theoretical calculations and experimental 1H NMR. The conformational preferences of this compound showed to be resultant from a complex interplay between the strengths of possible intramolecular hydrogen bonds, steric interactions, hyperconjugation, entropy effects and the overall dipole moments. The Ac-Ala-N(Me)2 derivative was used in order to simulate the effect of polar protic solvents in disrupting intramolecular hydrogen bonds involving the -NHMe group in Ac-Ala-NHMe.PostprintPeer reviewe

2D Chemical Drawings Correlate to Bioactivities: MIA-QSAR Modelling of Antimalarial Activities of 2,5-Diaminobenzophenone Derivatives

Two-dimensional chemical structures of a series of 2,5-diaminobenzophenone derivatives, some farnesyltransferase inhibitors, have shown to correlate with the corresponding antimalarial activities. The descriptors in this QSAR analysis are pixels of the chemical structures (two dimensional images) transformed into binaries and, therefore, the data variance explaining the variance in the activities block corresponds to the coordinates of each pixel in each molecule. This method, named multivariate image analysis applied to quantitative structure-activity relationship (MIA-QSAR), was applied to model the antimalarial activities of the titled compounds and the results were compared to well known three-dimensional QSAR techniques for the same class of compounds. In addition to the simplicity and high predictive performance of the MIA-QSAR modelling, this 2D image-based method has the potential of working well when equally simple, classical analysis fails. Overall, the present QSAR analysis based on 2D chemical drawings (constrained structures) dispensed conformational screening and 3D alignment to provide a reliable QSAR model; the physicochemical description about e.g. steric effects and chiral centers is all contained in the way in which substituents in a congeneric series are drawn, and the method can serve as a tool to introduce those who are planning to deal with drug design

Web-based Platform For Collaborative Medical Imaging Research

Medical imaging research depends basically on the availability of large image collections, image processing and analysis algorithms, hardware and a multidisciplinary research team. It has to be reproducible, free of errors, fast, accessible through a large variety of devices spread around research centers and conducted simultaneously by a multidisciplinary team. Therefore, we propose a collaborative research environment, named Adessowiki, where tools and datasets are integrated and readily available in the Internet through a web browser. Moreover, processing history and all intermediate results are stored and displayed in automatic generated web pages for each object in the research project or clinical study. It requires no installation or configuration from the client side and offers centralized tools and specialized hardware resources, since processing takes place in the cloud.941

Inter- and intramolecular CF···C=O interactions on aliphatic and cyclohexane carbonyl derivatives

The authors thank EaStCHEM and the University of St Andrews for access to a computing facility managed by Dr H. Fruchtl., CNPq, and FAPESP for the studentship (to R.A.C. #2011/01170-1, FAPESP) and for financial support (#2014/25903-6), as well as CNPq for the fellowship (R.R.).The assessment of weak inter- and intra- molecular Cδ+Fδ-...Cδ+=Oδ- interactions were theoretically evaluated in 4 different sets of compounds at different theoretical levels. Intermolecular CH3F...C=O interactions were stabilizing by ca. 1 kcal mol-1 for various carbonyl containing functional groups. Intramolecular CF...C=O interactions were also detected in aliphatic and fluorinated cyclohexane carbonyl derivatives. However, the stabilisation provided by intramolecular CF...C=O interactions was not enough to govern the conformational preferences of compounds 2-4.PostprintPeer reviewe